Senior AI Platform Engineer

Lirio is a technology/software company that provides expertise in a variety of behavioral science domains (e.g., behavioral economics, social psychology, public health), data science, and machine learning to drive consumer engagement, close gaps in preventive and chronic care, and promote health and well-being across an individual’s lifespan. Lirio’s behavior change AI platform unites behavioral science with advanced artificial intelligence (AI) to deliver Precision Nudging health interventions. Precision Nudging is the application of behavioral science to health interventions personalized by AI to each individual that overcome barriers to action at the right time and place for scalable, behavior change. 

This is a remote role with the opportunity to be hybrid if located in Tennessee. All applicants must be authorized to work in the US without sponsorship.

To ensure an excellent onboarding experience and integration into the company, new colleagues will spend their first week onsite at one of our offices in Tennessee. Travel expenses will be paid. This is a requirement. 

Position Summary 

The Senior AI Platform Engineer is responsible for architecting, building, and maintaining the agentic software execution layer within Lirio’s Precision Nudging Platform.   This position bridges the gap between MLOps and autonomous AI orchestration by engineering the workflows for AI agents to operate securely and reliably.  Key components of this role are AI workflow design, managing and optimizing the AI infrastructure and life cycle, assuring interoperability with Lirio Platform systems and client agents, and safety/governance of implemented AI systems.  The Senior AI Platform Engineer will collaborate in a cross-functional team that includes platform, cloud, security and machine learning research engineers, as well as system architects.  

Essential Duties & Responsibilities 

Agent Orchestration & Workflow Design 

• Design and implement infrastructure to support LLM-based autonomous agents capable of multi-step reasoning, planning, and task execution.
• Build and manage directed workflows using state machines and tools to coordinate complex AI-human handoffs.
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